Free University of Bozen-Bolzano

About: Free University of Bozen-Bolzano is a education organization based out in Bolzano, Italy. It is known for research contribution in the topics: Description logic & Recommender system. The organization has 1326 authors who have published 6011 publications receiving 117945 citations. The organization is also known as: Free University of Bolzano & Free University of Bozen.

Introduction to Recommender Systems Handbook

Abstract: Recommender Systems (RSs) are software tools and techniques providing suggestions for items to be of use to a user. In this introductory chapter we briefly discuss basic RS ideas and concepts. Our main goal is to delineate, in a coherent and structured way, the chapters included in this handbook and to help the reader navigate the extremely rich and detailed content that the handbook offers.

Tractable Reasoning and Efficient Query Answering in Description Logics: The DL-Lite Family

Abstract: We propose a new family of description logics (DLs), called DL-Lite, specifically tailored to capture basic ontology languages, while keeping low complexity of reasoning. Reasoning here means not only computing subsumption between concepts and checking satisfiability of the whole knowledge base, but also answering complex queries (in particular, unions of conjunctive queries) over the instance level (ABox) of the DL knowledge base. We show that, for the DLs of the DL-Lite family, the usual DL reasoning tasks are polynomial in the size of the TBox, and query answering is LogSpace in the size of the ABox (i.e., in data complexity). To the best of our knowledge, this is the first result of polynomial-time data complexity for query answering over DL knowledge bases. Notably our logics allow for a separation between TBox and ABox reasoning during query evaluation: the part of the process requiring TBox reasoning is independent of the ABox, and the part of the process requiring access to the ABox can be carried out by an SQL engine, thus taking advantage of the query optimization strategies provided by current database management systems. Since even slight extensions to the logics of the DL-Lite family make query answering at least NLogSpace in data complexity, thus ruling out the possibility of using on-the-shelf relational technology for query processing, we can conclude that the logics of the DL-Lite family are the maximal DLs supporting efficient query answering over large amounts of instances.

Context-Aware Recommender Systems

Abstract: Context-aware recommender systems (CARS) generate more relevant recommendations by adapting them to the specific contextual situation of the user. This article explores how contextual information can be used to create more intelligent and useful recommender systems. It provides an overview of the multifaceted notion of context, discusses several approaches for incorporating contextual information in recommendation process, and illustrates the usage of such approaches in several application areas where different types of contexts are exploited. The article concludes by discussing the challenges and future research directions for context-aware recommender systems.

The Effect of Audit Committee Expertise, Independence, and Activity on Aggressive Earnings Management

Abstract: This study investigates whether the expertise, independence, and activities of a firm's audit committee have an effect on the quality of its publicly released financial information. In particular, we examine the relationship between audit committee characteristics and the extent of corporate earnings management as measured by the level of income‐increasing and income‐decreasing abnormal accruals. Using two groups of U.S. firms, one with relatively high and one with relatively low levels of abnormal accruals in the year 1996, we find a significant association between earnings management and audit committee governance practices. We find that aggressive earnings management is negatively associated with the financial and governance expertise of audit committee members, with indicators of independence, and with the presence of a clear mandate defining the responsibilities of the committee. The association is similar for both income‐increasing and income‐decreasing earnings management, suggesting that audit com...

Process Mining Manifesto

Abstract: Process mining techniques are able to extract knowledge from event logs commonly available in today’s information systems. These techniques provide new means to discover, monitor, and improve processes in a variety of application domains. There are two main drivers for the growing interest in process mining. On the one hand, more and more events are being recorded, thus, providing detailed information about the history of processes. On the other hand, there is a need to improve and support business processes in competitive and rapidly changing environments. This manifesto is created by the IEEE Task Force on Process Mining and aims to promote the topic of process mining. Moreover, by defining a set of guiding principles and listing important challenges, this manifesto hopes to serve as a guide for software developers, scientists, consultants, business managers, and end-users. The goal is to increase the maturity of process mining as a new tool to improve the (re)design, control, and support of operational business processes.